|
|
Absolute deviation, 绝对离差
( T( M9 D d$ ]% sAbsolute number, 绝对数
$ F$ U- N4 P1 v! ?& eAbsolute residuals, 绝对残差; V3 p2 R1 V \0 {/ ]- f/ Q
Acceleration array, 加速度立体阵
6 z; ~ m* e3 W( b1 pAcceleration in an arbitrary direction, 任意方向上的加速度/ `- U1 p& c. K1 s$ D
Acceleration normal, 法向加速度
( j" q: H4 ^! u; QAcceleration space dimension, 加速度空间的维数
, h. F: Z, ? KAcceleration tangential, 切向加速度+ l1 O- c3 D4 s. R9 l# \
Acceleration vector, 加速度向量9 G' ]1 B, Q1 } a
Acceptable hypothesis, 可接受假设; S' U( p4 W! n l7 g5 g! ]' i
Accumulation, 累积% Q l: K0 m+ H) l" P
Accuracy, 准确度
& B% e3 X3 ^9 |* RActual frequency, 实际频数
9 F) g4 G) A& `) h/ EAdaptive estimator, 自适应估计量1 T4 X2 i5 J' N2 q
Addition, 相加! E/ h$ g$ F) s& Q5 x2 d
Addition theorem, 加法定理
$ }9 q+ L" C) ^" O8 H- CAdditivity, 可加性
% H2 E3 w f' T& wAdjusted rate, 调整率3 V- g7 I3 N' E6 f
Adjusted value, 校正值# X2 u+ y1 S: m5 L3 S: k# e
Admissible error, 容许误差3 z9 v9 b% |9 f6 `8 }; S6 o( {
Aggregation, 聚集性
3 s) N* u% S( V" u( n: L6 H4 }Alternative hypothesis, 备择假设- Z) N/ T( d) e# m
Among groups, 组间) w( q8 E% ]( ^ X5 p# h0 M
Amounts, 总量8 W/ E) O' D0 `
Analysis of correlation, 相关分析4 u7 a7 y8 P5 w' p& f7 S4 q
Analysis of covariance, 协方差分析
8 \" d9 _; _1 T) }Analysis of regression, 回归分析
" B7 {7 c0 W) p, W8 O: KAnalysis of time series, 时间序列分析; }: S/ H# z2 @3 ?' z
Analysis of variance, 方差分析( d2 H( _( ~, M% z9 j
Angular transformation, 角转换$ V% P; p( p- `9 S# K1 W; @
ANOVA （analysis of variance）, 方差分析' ^2 j* I* G( J
ANOVA Models, 方差分析模型
% y* Y% p5 F% A+ iArcing, 弧/弧旋
" {/ i0 d6 a" o2 v, t5 P% AArcsine transformation, 反正弦变换' W4 O1 G _% c
Area under the curve, 曲线面积7 N: G+ I6 c) q
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 * w$ Z* _0 V' _6 v
ARIMA, 季节和非季节性单变量模型的极大似然估计
) D5 x8 j. I* b% k4 FArithmetic grid paper, 算术格纸 t- g( x5 ]) q$ j( k+ S7 a! l
Arithmetic mean, 算术平均数/ r( N" r! @, M) `- f
Arrhenius relation, 艾恩尼斯关系
! h; Q$ ^4 t! G _Assessing fit, 拟合的评估
( C5 B4 p& s7 w/ I2 @( z7 JAssociative laws, 结合律
: _6 b4 H [8 q9 @& tAsymmetric distribution, 非对称分布
! H8 ~% A5 N) P" j" t+ Z; U tAsymptotic bias, 渐近偏倚
% h$ y+ [7 r9 ~* a+ Y, ]7 kAsymptotic efficiency, 渐近效率
4 L0 o) H2 d5 j( l+ g! C# DAsymptotic variance, 渐近方差# \' c+ x/ e6 A- _" w
Attributable risk, 归因危险度
4 z+ P: g+ _( k! @3 R5 H; bAttribute data, 属性资料
9 y" ?# i6 N2 k( N- d5 j; TAttribution, 属性1 `9 X0 B6 N1 L' N3 D: Z
Autocorrelation, 自相关
2 d- i1 l4 g+ J" m2 G; CAutocorrelation of residuals, 残差的自相关
1 i( y2 t; [7 v# ?! q3 R) b% Z! PAverage, 平均数
5 u( P' K d- B H G# PAverage confidence interval length, 平均置信区间长度
4 }/ M7 o3 {/ JAverage growth rate, 平均增长率
5 i) ~ N {. gBar chart, 条形图
& M |* a2 G* A6 B1 r5 kBar graph, 条形图' B# f8 ?* u+ d) ~
Base period, 基期( M* ^% G4 n' H/ s5 p
Bayes' theorem , Bayes定理
1 D4 c. I: K+ W! E1 YBell-shaped curve, 钟形曲线
5 P5 |! k' a3 O: k; D& R7 U! n" TBernoulli distribution, 伯努力分布$ A8 M) M3 c% {! W, r; [3 s
Best-trim estimator, 最好切尾估计量7 |* x, C" d) h! G; D" G0 E
Bias, 偏性; m+ O! z6 v7 V* H2 V9 i
Binary logistic regression, 二元逻辑斯蒂回归. h/ ?8 P" q6 p. U/ I2 [" }: i
Binomial distribution, 二项分布
2 o4 c4 t ]: g- ]* I7 KBisquare, 双平方
% U) m {8 r- ~2 mBivariate Correlate, 二变量相关
3 Y- C& {, J+ n4 ~Bivariate normal distribution, 双变量正态分布
5 r1 r% S/ l9 u4 X* }: O. L S" z6 YBivariate normal population, 双变量正态总体
- r6 N/ c9 b# K& q4 P, C) ]Biweight interval, 双权区间
5 `* _! l7 |; u9 s4 Q8 Y7 QBiweight M-estimator, 双权M估计量
7 m% K/ A: m% ~+ s# J6 J& I; fBlock, 区组/配伍组) k4 }6 W M/ b
BMDP(Biomedical computer programs), BMDP统计软件包
9 E& f0 F% Y' y8 ~Boxplots, 箱线图/箱尾图
3 Z5 T6 n( X. t) o- PBreakdown bound, 崩溃界/崩溃点& _0 W$ ]) r5 N
Canonical correlation, 典型相关
4 J& x4 {7 C- W# E \3 bCaption, 纵标目
4 M1 |7 {+ a7 R) i8 kCase-control study, 病例对照研究
4 t: o( w% b/ r( LCategorical variable, 分类变量' m% [3 f0 B1 k d: A0 z
Catenary, 悬链线
' U0 Y+ R; O- j/ _. w! BCauchy distribution, 柯西分布
/ A" W9 r- M5 p1 a( cCause-and-effect relationship, 因果关系- y' U. a- Y- f4 }" D/ k
Cell, 单元
& t, _" }% A* O0 h& G# kCensoring, 终检
1 w2 G. ^( p3 Z, mCenter of symmetry, 对称中心 I( ~* k. Q @" q/ b
Centering and scaling, 中心化和定标6 m+ E) x) r$ `- ]$ o' H; E7 {
Central tendency, 集中趋势( Q! P l1 R r4 q: A
Central value, 中心值& q+ B: h, U" E
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测9 b% D' `, x, S" G/ Q) X ^& A
Chance, 机遇+ D9 g# \6 G! w( B2 r v
Chance error, 随机误差
5 j6 j; i* c" f: wChance variable, 随机变量* }7 d; f- E- y. p( w* ^! Z
Characteristic equation, 特征方程8 B5 f, W/ N" c% n$ c M9 i
Characteristic root, 特征根4 q3 H8 @4 \% j- k; ]+ `4 w- E
Characteristic vector, 特征向量' I- o! m! l f5 ]0 p8 }4 F
Chebshev criterion of fit, 拟合的切比雪夫准则+ _4 L4 l- `; b. {( t0 a/ m: b9 u
Chernoff faces, 切尔诺夫脸谱图
; c% k* m4 L. b$ s$ h* X% ]8 OChi-square test, 卡方检验/χ2检验
! i! T& T# o* p" J I" O! mCholeskey decomposition, 乔洛斯基分解9 k1 }6 G$ h' P, ~5 d
Circle chart, 圆图
/ a5 u7 P% X9 s- j; r2 L# y3 NClass interval, 组距
0 f# Y8 m4 N9 \2 O/ pClass mid-value, 组中值4 W* N) \1 c4 N1 @
Class upper limit, 组上限
/ ~* @- l" p' MClassified variable, 分类变量
1 N' r i4 p- p' K- mCluster analysis, 聚类分析 n2 E8 Z" d3 b# @. y9 l
Cluster sampling, 整群抽样
5 J- C8 e# M& C& Q/ d. z9 [' ICode, 代码+ X7 X8 p( t5 s3 C8 @0 T4 g
Coded data, 编码数据' `$ Q4 i9 h$ Y! }
Coding, 编码) K$ e6 B+ I, j
Coefficient of contingency, 列联系数
) _+ f" Q4 S. U @Coefficient of determination, 决定系数 r- _9 d% Q1 S+ M
Coefficient of multiple correlation, 多重相关系数% d/ E7 G% g8 o1 X
Coefficient of partial correlation, 偏相关系数; q. r3 d) Q y6 G2 {
Coefficient of production-moment correlation, 积差相关系数8 q0 F5 ?: j! T: ~4 U- Z
Coefficient of rank correlation, 等级相关系数
3 Q( W% ^8 f9 ]9 d) ^0 tCoefficient of regression, 回归系数8 e( i: _% R) t: r
Coefficient of skewness, 偏度系数
( l6 x2 y E0 V" S e7 e0 K M8 w% {Coefficient of variation, 变异系数
* j0 N; n, P% {4 ^$ JCohort study, 队列研究7 f, p( y: C: u$ ]5 F
Column, 列' I/ A& N. _; s3 N! G9 g
Column effect, 列效应
% a, X5 l o$ q$ v5 |5 E8 s1 O* JColumn factor, 列因素, s) }( c' h4 B3 ]* u/ H
Combination pool, 合并
7 m4 f6 N& F5 cCombinative table, 组合表
. ]! @( ~0 N. _! f' T) E& a0 w2 uCommon factor, 共性因子" Q* |8 D2 g1 \6 }, s* \/ Q8 j7 F4 R
Common regression coefficient, 公共回归系数
9 n# t! Y- b1 p1 c6 P+ U2 C" \Common value, 共同值
6 z9 w7 T) Y3 n. I* S4 @Common variance, 公共方差
& I* \0 t/ e6 ^! w$ DCommon variation, 公共变异
- \5 y2 l D7 D% G0 o OCommunality variance, 共性方差+ L4 Y2 c( H" h; u4 q: J
Comparability, 可比性6 p: F" V: \' `1 b/ d, ]7 [
Comparison of bathes, 批比较
3 w: K( U( s' J$ [8 U1 {Comparison value, 比较值
0 s1 ]1 K8 L, C4 Y. C, d8 D2 tCompartment model, 分部模型
0 `# m) z% Q6 [+ {% qCompassion, 伸缩) k4 x; l' D) T; @. ^+ R
Complement of an event, 补事件
" r! [7 B5 I* _4 v6 e2 N8 PComplete association, 完全正相关7 e* C2 f! Z* r; d( g
Complete dissociation, 完全不相关8 x; r @: I1 m+ A8 @
Complete statistics, 完备统计量
7 M0 v7 [$ i9 C$ |% U- D4 ^Completely randomized design, 完全随机化设计- w3 M8 s9 M5 N2 f
Composite event, 联合事件
' i. T& P3 K. ], ]Composite events, 复合事件
& d+ D8 A0 a& ~7 K/ X* CConcavity, 凹性1 g% F; U" n, O$ G
Conditional expectation, 条件期望
0 g9 A9 ^ g" p; C+ H G1 _Conditional likelihood, 条件似然
^% c1 d2 b1 f2 e& K' w! l/ nConditional probability, 条件概率
3 p. T9 K2 _) R, ]Conditionally linear, 依条件线性
- I, Y! @8 O: x5 }7 aConfidence interval, 置信区间
6 k, g+ K. R& }% v- B; h# l. YConfidence limit, 置信限9 W/ }/ l: b' R: V b R5 [ X
Confidence lower limit, 置信下限
. Y6 V! K* ^. u; X4 v9 AConfidence upper limit, 置信上限
3 M3 \0 ?" X$ T- sConfirmatory Factor Analysis , 验证性因子分析
$ m0 R- l3 u. I1 Q! [! iConfirmatory research, 证实性实验研究- I: c$ W7 r9 J1 u: }
Confounding factor, 混杂因素
% I3 n) l2 t; |7 qConjoint, 联合分析
! g! p1 D7 F7 i, w; _3 e$ FConsistency, 相合性
. H4 a( W2 }+ u# X+ h |; ~Consistency check, 一致性检验- v y7 V# Z* _; u
Consistent asymptotically normal estimate, 相合渐近正态估计
/ c. s7 ?) o# u4 CConsistent estimate, 相合估计
Y# \6 \- x. }& G7 W# ?( UConstrained nonlinear regression, 受约束非线性回归2 G6 Z/ S2 R1 Y$ L; ~7 r' Y; M- B0 D
Constraint, 约束
4 ?4 s3 \. ]! dContaminated distribution, 污染分布
# x, `$ t) ?* V4 O; aContaminated Gausssian, 污染高斯分布
! D, J: S5 A; d t: s, t: [Contaminated normal distribution, 污染正态分布) i8 |1 l. B- E/ O
Contamination, 污染
6 x7 W, G( C6 i3 b( H; \Contamination model, 污染模型4 e( o) }' b) D
Contingency table, 列联表+ M0 u+ \# Z5 m' B
Contour, 边界线* o8 y4 G2 ~; f7 a* M& B6 T9 Z
Contribution rate, 贡献率! T' R+ }) \! W# d2 Q4 J
Control, 对照
+ T- }% E# [. K L3 \. zControlled experiments, 对照实验
( c& f7 T/ H" q% Y6 O/ x. `' bConventional depth, 常规深度. ?# T. Z( ^/ l4 u
Convolution, 卷积
/ w, a9 e, D- g5 {& s9 \Corrected factor, 校正因子
, w7 \8 V7 V9 \! i1 rCorrected mean, 校正均值
* q( m8 D* Q; @( v6 A$ ICorrection coefficient, 校正系数' \9 E. K) R% E" q
Correctness, 正确性1 b+ d# |6 H- B" }# D/ w4 `
Correlation coefficient, 相关系数; w$ D Y) m1 ?' ~3 r9 r
Correlation index, 相关指数% P* Y8 J t1 |! {/ T% {
Correspondence, 对应
& G/ f" ^ |; t: hCounting, 计数
- W8 q! N. |- fCounts, 计数/频数) V' H# B# K- u1 D5 L0 S# W$ ?% b
Covariance, 协方差
, ~2 N8 X: w9 U0 y- k& n) }! U+ FCovariant, 共变 : K" d! P( q" F$ |, O2 d
Cox Regression, Cox回归% J+ z7 m) v" L& Q. N& m* S
Criteria for fitting, 拟合准则8 L# h+ U; P w5 t' O- n5 ?
Criteria of least squares, 最小二乘准则+ t: v8 _9 T* K- X
Critical ratio, 临界比
. _) V$ D7 E& M% P. xCritical region, 拒绝域
% u3 c; x8 G n) v6 {% l' rCritical value, 临界值( O6 ^& g9 E2 I- K
Cross-over design, 交叉设计3 R$ H/ H" U% r; H% s0 K' j
Cross-section analysis, 横断面分析. ^/ S9 }; O+ K+ f# O ^
Cross-section survey, 横断面调查$ l" T/ @2 e6 P
Crosstabs , 交叉表 ! _8 U& r+ \( S* ?* L
Cross-tabulation table, 复合表7 p! w! K/ {, ` ?5 [
Cube root, 立方根
8 w$ m. Q1 D" z* b. ZCumulative distribution function, 分布函数
1 d7 W( n# y' VCumulative probability, 累计概率
, G k, x! a% J7 C/ e! ZCurvature, 曲率/弯曲
) h; S# b* V# b6 V% l% [Curvature, 曲率
) w/ C6 V3 V* C+ z: \Curve fit , 曲线拟和
5 W' Y: }# ~4 n0 ECurve fitting, 曲线拟合% k% t) D3 |2 S R9 m8 Q) z/ M7 W% |
Curvilinear regression, 曲线回归' K3 k# X' g9 P
Curvilinear relation, 曲线关系
8 F- q8 p3 g3 z7 V! R7 p) gCut-and-try method, 尝试法0 y- V! s5 }" H5 n
Cycle, 周期
! f+ s5 V5 X3 C1 C4 t2 rCyclist, 周期性2 B1 @* c; W5 ~5 i" @0 Q- W
D test, D检验, x* x* I7 c, N9 V# ^) X P6 q
Data acquisition, 资料收集% K! R1 L: J/ l9 G8 ~ v# h
Data bank, 数据库; c: _9 i `# m9 H
Data capacity, 数据容量1 X; d6 d# ]3 C3 T# n
Data deficiencies, 数据缺乏
% ?4 a9 c/ ] WData handling, 数据处理
) M$ \1 I: d8 r( b0 yData manipulation, 数据处理% T+ y( U1 e1 Z1 t
Data processing, 数据处理) t: j) W8 q' L8 }
Data reduction, 数据缩减, b7 T) F$ R$ s' n- G
Data set, 数据集, `8 s+ ~3 u0 q% A/ T- e% \$ f
Data sources, 数据来源4 [8 ~( C5 p' j8 R/ Q
Data transformation, 数据变换
( M* f& `8 \% ?3 S5 \+ [Data validity, 数据有效性: a X, o D# K* m+ I$ x/ t$ o
Data-in, 数据输入* m4 R9 Q% D" O& n5 q
Data-out, 数据输出
* ^& f6 |& K( w* D1 QDead time, 停滞期1 I+ k. Y7 M1 S* S3 I( F! S
Degree of freedom, 自由度
, o: G/ m' }! ]8 t1 s7 JDegree of precision, 精密度1 t! @* P Z9 b$ R4 \8 m3 K2 P
Degree of reliability, 可靠性程度
! M* {8 u' l5 pDegression, 递减
y' W- A4 t- f4 V! T- q# D7 CDensity function, 密度函数
! F7 N: ~+ [3 z* \5 c7 wDensity of data points, 数据点的密度0 E6 u4 w/ I2 Z' _) Z
Dependent variable, 应变量/依变量/因变量
; v, E6 X' [: VDependent variable, 因变量
9 C/ ]# }% l1 hDepth, 深度
P$ y5 l( |( L& [Derivative matrix, 导数矩阵0 \6 U ^% ~8 b
Derivative-free methods, 无导数方法2 Q- o2 t& b# u7 _% d/ r9 `
Design, 设计; ~% b" i4 z6 J$ E$ v4 b2 P: q2 m$ n
Determinacy, 确定性6 j, \4 J- ^+ a, g6 L; N9 x/ M
Determinant, 行列式& [: H2 H/ {$ N [& D; y8 O
Determinant, 决定因素! z! Q5 p( [1 D8 e+ _+ {" B
Deviation, 离差
( r! E2 Y& C3 O& J2 W% wDeviation from average, 离均差
8 ~+ j% a& \+ n; j, x/ }/ ?Diagnostic plot, 诊断图1 w2 y# \* l" q L- j
Dichotomous variable, 二分变量
: @9 ?- Z- e+ K' V) w% [& qDifferential equation, 微分方程4 [- Q3 g4 Z; Q1 {1 J
Direct standardization, 直接标准化法
3 P# Z% h" \+ }; F7 a5 n6 V" J& \% [Discrete variable, 离散型变量
6 V- F$ `0 s& y" I( P- N0 {DISCRIMINANT, 判断
R) ^, Z7 M; t4 M6 BDiscriminant analysis, 判别分析8 `- V8 {6 M, p* |- g" C- ^
Discriminant coefficient, 判别系数0 H! g" e6 W" C
Discriminant function, 判别值1 ~- E" T6 `1 i' A+ {
Dispersion, 散布/分散度2 x: y3 F- O& `* n
Disproportional, 不成比例的
. A# h+ Z# F# B& t1 b+ LDisproportionate sub-class numbers, 不成比例次级组含量
( J+ i$ h9 r" @8 x/ j5 _ zDistribution free, 分布无关性/免分布& v. U0 @) r: ]# b3 L' z
Distribution shape, 分布形状
- r0 `+ q2 @8 @Distribution-free method, 任意分布法
7 d* U. I: U6 P* n) HDistributive laws, 分配律
8 [. Z* Q$ P. E6 W' aDisturbance, 随机扰动项
: J" [/ D9 \, J0 b- @' [# @% lDose response curve, 剂量反应曲线
. R" y4 ?# S9 B. L! lDouble blind method, 双盲法7 z5 F# A, x' C5 l+ G( g5 {
Double blind trial, 双盲试验
9 a) v) r+ e1 y RDouble exponential distribution, 双指数分布! d" Q3 O5 O8 S# p$ T
Double logarithmic, 双对数! y3 H9 W$ }+ y" f3 Q' w% f
Downward rank, 降秩2 J( r7 _8 o6 t) h
Dual-space plot, 对偶空间图
) a6 I+ i1 r9 r0 {0 p# cDUD, 无导数方法: _- i9 ^- ~4 ?" r
Duncan's new multiple range method, 新复极差法/Duncan新法! y; D0 Q- y) I; H/ z* L, u! |
Effect, 实验效应
m6 n6 {) @2 yEigenvalue, 特征值
1 H5 _ U9 s' ]* k3 f, UEigenvector, 特征向量
# u# `# H4 g5 D' r; W' W. @Ellipse, 椭圆* {$ s2 W: _- h( d
Empirical distribution, 经验分布6 d! B# D. A x8 o1 i
Empirical probability, 经验概率单位
' I% T0 X- e4 U/ K0 I; \8 s/ MEnumeration data, 计数资料
1 `. [. I6 O& f, X/ GEqual sun-class number, 相等次级组含量
% i" e1 D2 q8 E" Y% y/ S( wEqually likely, 等可能0 `) P s( [" s" d6 V5 ?
Equivariance, 同变性6 G u" ~; w. y# g2 B
Error, 误差/错误6 Q6 ~* M5 ~. ] Z: Z: `; ~
Error of estimate, 估计误差
+ I5 C9 \5 D0 i% k1 ^& W: hError type I, 第一类错误
5 Q7 e1 k3 d3 {. B/ @: gError type II, 第二类错误
/ r7 l; O% i+ W- ~6 {# o# IEstimand, 被估量& J' A( Z9 z( k/ o; v
Estimated error mean squares, 估计误差均方* Q2 h& O% h" j2 G3 r
Estimated error sum of squares, 估计误差平方和/ e$ S+ _7 p5 K4 q
Euclidean distance, 欧式距离
) e6 ?' {3 u& Z. z$ QEvent, 事件
3 B: w% b) K& L" x! TEvent, 事件
4 m- u& s4 }1 h5 s9 LExceptional data point, 异常数据点, @1 D6 g/ ?; S& e6 R" N. a; Y
Expectation plane, 期望平面
4 Q& n$ `, L# S% J1 g/ o7 EExpectation surface, 期望曲面
8 @+ l4 }; [& p# m# q' rExpected values, 期望值
' `6 e# |6 d* Q2 @5 {% |Experiment, 实验
, q6 O- ]1 L# S6 K6 [& Z8 fExperimental sampling, 试验抽样
! T9 f, l3 j8 z! _Experimental unit, 试验单位
9 R; A+ {7 N& U% h# vExplanatory variable, 说明变量
2 f) M5 s/ M* l3 M- gExploratory data analysis, 探索性数据分析 z$ Y* M2 f/ W, ^6 N8 z3 P! U
Explore Summarize, 探索-摘要
7 Q( M+ J6 s, `: z- O5 t' n vExponential curve, 指数曲线
5 @4 A. R o3 C4 ?3 {Exponential growth, 指数式增长
9 {: q) r% a& z$ z. q) R8 B1 nEXSMOOTH, 指数平滑方法
|; M0 x' N% \" m) g# W5 ]* jExtended fit, 扩充拟合
, N2 Q) ? G' U! @: w3 nExtra parameter, 附加参数' ?5 x; u& i9 s% E% F0 K
Extrapolation, 外推法
# N/ k9 z# f6 I& c( ZExtreme observation, 末端观测值: Q& a! F D7 l! b
Extremes, 极端值/极值
& P2 i( }/ P; I( hF distribution, F分布
& x5 {8 a, p( s8 l! U, p: rF test, F检验
. a3 w3 F8 m. X5 ~Factor, 因素/因子
* A( }# s( w3 tFactor analysis, 因子分析0 b! S4 t {+ ]! E/ _
Factor Analysis, 因子分析
/ X) T/ K6 \& qFactor score, 因子得分 $ i! }' W+ C# |' M6 l% o
Factorial, 阶乘
7 C$ w. P9 t% vFactorial design, 析因试验设计
% V. n6 d |: t9 }+ D, s, b; K# nFalse negative, 假阴性
$ Z1 x% z5 @; Y: t) T2 }, Z# }' xFalse negative error, 假阴性错误/ h3 n8 D- @6 M7 k( [* G& U
Family of distributions, 分布族
4 o+ X) Y( v0 V2 T @" B# @Family of estimators, 估计量族
& a9 |- v, q: [$ d8 d1 lFanning, 扇面
2 `; @/ g" Y' j5 S6 r3 \Fatality rate, 病死率' g A; k! j9 h
Field investigation, 现场调查; ?8 D: b2 V. C% m& ~: H
Field survey, 现场调查
1 I' `/ N I" E) ^Finite population, 有限总体$ j7 p8 W7 G6 d5 Q8 h( y
Finite-sample, 有限样本+ M5 y# k3 H9 Y3 ?: r; b- l
First derivative, 一阶导数! @/ L: l5 M$ F! d2 b+ g
First principal component, 第一主成分
0 c* O K6 G+ K* K, `: L' aFirst quartile, 第一四分位数
5 C* p% O/ _% l/ K" {3 ]/ dFisher information, 费雪信息量
3 Q# f% z" v4 `, k) g5 _# wFitted value, 拟合值
9 Y- ^& ]; ~' jFitting a curve, 曲线拟合
. M5 B: k3 S, X1 W# U( O7 bFixed base, 定基
g1 l; c5 ]6 p" [Fluctuation, 随机起伏' L: t- {: a- l- m4 t# k
Forecast, 预测3 F5 o) s3 U F* v: B% d) Q
Four fold table, 四格表- j$ P- Q/ \8 ~! S2 ?
Fourth, 四分点
( v- \+ l2 V: B" V) r# YFraction blow, 左侧比率
& ?0 F7 z+ p* m* W( OFractional error, 相对误差9 k/ j0 j8 d" _6 e
Frequency, 频率4 r/ J! e* @, r! M# o6 J. a R
Frequency polygon, 频数多边图
4 \8 ^: l% a0 JFrontier point, 界限点8 c8 D% ~/ w/ B$ A1 _
Function relationship, 泛函关系
" g/ D9 R& g0 t5 f! z7 _/ B0 ?Gamma distribution, 伽玛分布
# b- m/ W# ~4 C6 G6 w5 `Gauss increment, 高斯增量
0 E# e# o" N, X B6 K( gGaussian distribution, 高斯分布/正态分布
! S% t/ y' w6 jGauss-Newton increment, 高斯-牛顿增量
' ?9 l% C3 T1 A2 a" @ n7 K, KGeneral census, 全面普查
' p) H' L2 C7 M F8 mGENLOG (Generalized liner models), 广义线性模型 - E) f; {% {" C5 Y3 N
Geometric mean, 几何平均数- o0 i# J) x: G+ J. E- G3 D0 @ l
Gini's mean difference, 基尼均差: L: C+ C L. u0 C$ r# g: u
GLM (General liner models), 一般线性模型 / H) Q0 T% F2 W: o# x9 n( @: v
Goodness of fit, 拟和优度/配合度* j- \8 p' U& ?0 c$ v* a r( g! {
Gradient of determinant, 行列式的梯度
$ c6 c" B" ^; n L! @8 T" [& CGraeco-Latin square, 希腊拉丁方
- y& f) F5 l* q, X& J4 C& KGrand mean, 总均值
3 C0 v$ K* b) d( LGross errors, 重大错误
$ ^8 h# _* O eGross-error sensitivity, 大错敏感度- ?$ i/ W, z/ N
Group averages, 分组平均
+ O+ `" q& A. [8 b- o: W& qGrouped data, 分组资料
( l6 `" d; v) }7 ^' g$ p, A0 jGuessed mean, 假定平均数
: R9 W: ~; Q' m$ f mHalf-life, 半衰期
/ i6 \, s3 f( {- q7 lHampel M-estimators, 汉佩尔M估计量* W1 ?. X3 U i& l; G
Happenstance, 偶然事件( ]. ~) E- \ Y& v4 l# I
Harmonic mean, 调和均数/ M; r. `; N$ w& D% ^ a
Hazard function, 风险均数2 d/ A2 z. G, S3 p
Hazard rate, 风险率
* N3 G2 d- |7 o8 O0 J( bHeading, 标目
0 j$ p7 r' H9 W2 p* ]) T# G% E: VHeavy-tailed distribution, 重尾分布
+ J, ]3 |1 M; S* Y0 i1 mHessian array, 海森立体阵
6 x: k) y1 q1 J, NHeterogeneity, 不同质
) H, D( @" u1 F- [ z; F. YHeterogeneity of variance, 方差不齐 / U6 ^2 S- |! n, ^1 j( E
Hierarchical classification, 组内分组
4 ?- `5 p: [ ~1 k' B% IHierarchical clustering method, 系统聚类法
2 p9 O7 S$ f tHigh-leverage point, 高杠杆率点4 O3 u% \: p; N- n% p" s' r
HILOGLINEAR, 多维列联表的层次对数线性模型$ `; ^/ z( o/ S# ?; n) b" |
Hinge, 折叶点
" W+ K, H7 }8 a: g2 Y" DHistogram, 直方图
9 X% t. z; P% V i: e7 N& jHistorical cohort study, 历史性队列研究
5 k- H4 E6 J4 A$ o0 _. a3 EHoles, 空洞
) ], M! {% E b/ H4 MHOMALS, 多重响应分析
* g" n5 ?; k. G* B' DHomogeneity of variance, 方差齐性
& H% C! x9 D" u) [Homogeneity test, 齐性检验- R% h7 n& k* w$ Z& X: d2 O( M7 c
Huber M-estimators, 休伯M估计量* v1 K2 G7 Y, C+ [7 g. q3 s0 |
Hyperbola, 双曲线
4 b# q6 W; T% \6 BHypothesis testing, 假设检验
( v) m: L% X- t1 l( b1 N. g% LHypothetical universe, 假设总体2 [3 p6 n' E. z
Impossible event, 不可能事件
8 R3 A( n7 [" s/ L$ y/ r8 I7 t: hIndependence, 独立性8 }% L5 O; E& q9 k7 @! n% r
Independent variable, 自变量/ T8 N' Z% @* F- b: H
Index, 指标/指数
) W2 _3 w% t2 f$ V2 tIndirect standardization, 间接标准化法
) K) {$ `4 c/ ]- L2 I1 CIndividual, 个体
9 S1 m- Q& i1 K+ `5 ]0 p! ]) JInference band, 推断带& D; I. c5 B; ^1 P( m8 H# ]
Infinite population, 无限总体
' j' a l1 S; Y* i0 r2 OInfinitely great, 无穷大
- G3 Q% P2 q! H2 P( w/ _- W6 o6 FInfinitely small, 无穷小
; h9 s3 F* q6 C* x, j# bInfluence curve, 影响曲线
9 o! n. a0 t% e' R9 w+ J$ \% aInformation capacity, 信息容量
% i$ i n0 D- }+ aInitial condition, 初始条件0 }; O! \$ Y8 H% c
Initial estimate, 初始估计值% A" d. K$ _% K/ w; ~$ ?3 y; T
Initial level, 最初水平
! J. w. |6 l) ~! w8 ]% v% kInteraction, 交互作用
! l$ v0 H( H+ W- o4 XInteraction terms, 交互作用项- O8 M4 m" u( H% A3 i
Intercept, 截距
3 Y7 k; [ R3 g2 i" WInterpolation, 内插法
7 `. d/ A9 Z' }Interquartile range, 四分位距
/ c9 u* {) B( A+ ]( KInterval estimation, 区间估计
% {8 d. j5 V" v/ {$ vIntervals of equal probability, 等概率区间
" c' _) a" `& MIntrinsic curvature, 固有曲率+ @+ {" L+ t; k* e" a1 L% \4 q
Invariance, 不变性% O+ i3 R4 w2 Z/ @
Inverse matrix, 逆矩阵
# P" [% t( R/ ]) F+ T2 B6 sInverse probability, 逆概率; Z5 \ N! @( E* |% ^6 n( w$ {" J
Inverse sine transformation, 反正弦变换/ U4 ?0 K6 i, a
Iteration, 迭代
1 Q1 S4 p5 i) x/ D/ t1 y2 \Jacobian determinant, 雅可比行列式0 a' p i$ z8 O- t% \5 C
Joint distribution function, 分布函数
9 V( _% N* S* [! M! e4 @Joint probability, 联合概率9 D) Y3 K* K% y* S/ x, n
Joint probability distribution, 联合概率分布) ~- e; T: e, R
K means method, 逐步聚类法
0 w: v% n9 l" p5 wKaplan-Meier, 评估事件的时间长度
1 e( L4 t* ^2 R$ A9 ZKaplan-Merier chart, Kaplan-Merier图" I& q' e) ^1 m- Q% q. B' C
Kendall's rank correlation, Kendall等级相关+ `& d4 O8 }6 V: S
Kinetic, 动力学0 J. J' G( N% `/ V, [; E/ }" v
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验! X6 X% v& ~. C5 b$ D" h1 y
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
2 l# ]3 a/ s* o; K6 Z. XKurtosis, 峰度
' }& [6 ~ `8 `6 XLack of fit, 失拟
' [0 I$ } B' }3 D6 rLadder of powers, 幂阶梯
) \ O* `: I) U8 S sLag, 滞后1 t6 j5 n! U3 c; l7 U
Large sample, 大样本
$ @+ Q: k% y$ S, N* W: a- eLarge sample test, 大样本检验" p1 e/ b6 y5 p$ T0 ], W/ ~3 ?" b( D" k( X
Latin square, 拉丁方1 u6 m5 \; m3 V, S& Y; g# i. O* ^
Latin square design, 拉丁方设计8 ^- M2 e1 b1 C
Leakage, 泄漏
9 }9 H1 _) v5 b# A$ T- H/ d5 KLeast favorable configuration, 最不利构形
8 w. U& o P7 J. oLeast favorable distribution, 最不利分布
5 h$ s! M- t: B. @! eLeast significant difference, 最小显著差法7 T6 Z% L8 w! J5 O. _( U" z* `
Least square method, 最小二乘法
! K% Z; a$ I- r2 G% ^1 M& HLeast-absolute-residuals estimates, 最小绝对残差估计. i* z7 f: g( s- |
Least-absolute-residuals fit, 最小绝对残差拟合: ^( c- T( Q7 F# ]* t+ \% U
Least-absolute-residuals line, 最小绝对残差线
6 M, M% g7 X/ h$ sLegend, 图例
, \: R* G5 w( `4 X) ML-estimator, L估计量 l( I& ]+ K! i0 L) I' K3 ~
L-estimator of location, 位置L估计量
9 q4 h, w9 l$ }3 l( yL-estimator of scale, 尺度L估计量
8 J! D6 X; m) E, D5 y: K6 Y6 p( tLevel, 水平" e6 k3 }/ f/ p+ G
Life expectance, 预期期望寿命
$ A# n6 V/ S. N3 D' H! I( b2 A4 hLife table, 寿命表8 h0 q% h' {( I
Life table method, 生命表法& {$ ^" W( B8 Y. l" A
Light-tailed distribution, 轻尾分布
6 `# i3 p' N# F/ OLikelihood function, 似然函数
- {3 |. k& v7 \Likelihood ratio, 似然比4 r1 r) b5 G. t" |2 y% j4 r6 c# t
line graph, 线图
8 _# f& N0 B9 E# k3 |6 MLinear correlation, 直线相关
% ~/ l$ q J! w X$ h; A. o* ?Linear equation, 线性方程
3 }- `7 ?2 y q9 Y' J# sLinear programming, 线性规划. t0 K" }) B% s3 J1 f* y
Linear regression, 直线回归8 Y4 c' b& `$ r, T: a
Linear Regression, 线性回归
( n: z" ]: f- ^- kLinear trend, 线性趋势3 A) O/ P5 m/ N3 P5 d0 ?
Loading, 载荷 0 M! }) T& ^ N0 m
Location and scale equivariance, 位置尺度同变性% ~' }8 I6 l, V: g& p' f
Location equivariance, 位置同变性
n. o' V9 x+ i* FLocation invariance, 位置不变性 Z7 Z; z( K3 ~6 ]
Location scale family, 位置尺度族) r' p$ f. S# `5 v B
Log rank test, 时序检验 1 ^9 R# d8 I( l- C: F; l8 l4 y) g
Logarithmic curve, 对数曲线9 W; w! o9 q* B0 ]% k$ r
Logarithmic normal distribution, 对数正态分布
0 J$ }1 R }& q( Y. C1 |) U0 V# K0 ELogarithmic scale, 对数尺度
% o! |# D5 z& @4 [) ?! SLogarithmic transformation, 对数变换
% L9 D# x! I1 S+ Z3 M# z% \Logic check, 逻辑检查" X: @ o' H9 E# L0 f% M* F [% I, i
Logistic distribution, 逻辑斯特分布
: x. X6 r: H0 Y4 M# \% dLogit transformation, Logit转换
6 d5 X i o$ `LOGLINEAR, 多维列联表通用模型 1 C% B' i8 z. F" t3 X' Y0 v
Lognormal distribution, 对数正态分布+ z2 E) [9 i0 l% `9 K7 _7 G) {
Lost function, 损失函数
, K* z4 C9 i) }3 h, e; G+ N7 OLow correlation, 低度相关
8 F, n8 p" U/ x, yLower limit, 下限
% }) C5 z( J4 h: jLowest-attained variance, 最小可达方差% F" c8 V+ }' A4 }/ [6 ]
LSD, 最小显著差法的简称9 {8 Q& {- Z/ a; @ h# u
Lurking variable, 潜在变量
9 u: y. L$ O0 ~Main effect, 主效应! `: I5 o& i Z/ d S
Major heading, 主辞标目+ j; ]1 x9 K8 Y
Marginal density function, 边缘密度函数1 ]' k: e7 G0 s4 I! I
Marginal probability, 边缘概率0 @, e1 x0 B4 N% `
Marginal probability distribution, 边缘概率分布8 A- F* |+ M; j6 e) F
Matched data, 配对资料
, h; ~4 f- g. U( p6 @- s' O; jMatched distribution, 匹配过分布* N, x6 I% R/ o5 @ T
Matching of distribution, 分布的匹配% f3 @- v+ n# H ] {+ ?7 t5 O
Matching of transformation, 变换的匹配% J! ?* V6 X& }' y6 b
Mathematical expectation, 数学期望* n* A, e+ X+ Z% E# A! r2 v) j
Mathematical model, 数学模型# u$ ~$ d1 a: O- l4 E: [% P. L
Maximum L-estimator, 极大极小L 估计量
5 H9 X+ @7 z( o$ r, hMaximum likelihood method, 最大似然法5 N+ _. ^# ]0 [, q. l+ X" D3 }
Mean, 均数% ` I7 f ?' X9 n9 \4 \2 g" Q
Mean squares between groups, 组间均方1 B2 M4 C' Z0 z$ ~4 ]2 u. a
Mean squares within group, 组内均方2 S, F; x5 K$ K( U2 ^$ \1 o D3 a
Means (Compare means), 均值-均值比较9 f* Z1 O8 O3 \; M+ X `) [' y
Median, 中位数3 G1 |3 T W( {: u
Median effective dose, 半数效量# S$ F4 O0 ^$ J
Median lethal dose, 半数致死量
1 l& X' _8 E5 `* G7 z6 K, aMedian polish, 中位数平滑
, D2 S/ I$ w3 |; fMedian test, 中位数检验6 i3 e: d" L! c9 r4 L+ l
Minimal sufficient statistic, 最小充分统计量
' r) K( [) E) R2 IMinimum distance estimation, 最小距离估计
; z, s6 O$ W) U% F! H. }Minimum effective dose, 最小有效量 u, z2 J9 S' p1 B( ^& k
Minimum lethal dose, 最小致死量
, [: `2 h# C& PMinimum variance estimator, 最小方差估计量
) v5 x3 T: ]# i' UMINITAB, 统计软件包
. K' }/ q5 C' A8 oMinor heading, 宾词标目% f' |1 l- y) A- X% q/ h( p1 o z$ b
Missing data, 缺失值
7 b: z" j- _6 D KModel specification, 模型的确定2 G/ N* f0 b4 t7 I, R3 k6 q8 S1 n
Modeling Statistics , 模型统计
" C5 H% v B" N( a( x7 @Models for outliers, 离群值模型
- K+ ~' a$ [* CModifying the model, 模型的修正
, `# P3 b- d8 _1 j& W. G5 @: M8 oModulus of continuity, 连续性模+ N7 C/ R- i6 K% Z, h
Morbidity, 发病率
, T+ A1 [2 P5 z( G) vMost favorable configuration, 最有利构形
4 Y( r5 a7 U+ s! \( mMultidimensional Scaling (ASCAL), 多维尺度/多维标度
9 ]1 t, M6 h0 OMultinomial Logistic Regression , 多项逻辑斯蒂回归
2 V' N) [6 h2 O a6 P Q4 DMultiple comparison, 多重比较! j; d. {, i7 ^! Q$ y
Multiple correlation , 复相关' U0 i! B2 H, A. [
Multiple covariance, 多元协方差
. Y1 z) c% Z: W, u: Y% I: iMultiple linear regression, 多元线性回归
# ^' b/ e r- ZMultiple response , 多重选项& T8 q. A# S+ X* p2 S* m+ f
Multiple solutions, 多解
0 V j5 ?) Q0 I# F$ L x8 U- hMultiplication theorem, 乘法定理
. _( D: ^4 ]" Z, \3 o5 j/ \Multiresponse, 多元响应
& u1 X2 o9 z# iMulti-stage sampling, 多阶段抽样- [' ~5 O. Y4 M3 H% q% W
Multivariate T distribution, 多元T分布
* X6 @- v6 c' T9 T- c8 b$ wMutual exclusive, 互不相容3 B+ q+ @* D$ l% H7 }$ ^! f: m
Mutual independence, 互相独立
) V0 e1 o! y% ~1 R& ZNatural boundary, 自然边界9 e5 t+ Z7 G2 Q' m( g* \
Natural dead, 自然死亡
) i: i, M- Q9 F! i3 u kNatural zero, 自然零
4 h& `; c$ |' }7 B* K0 dNegative correlation, 负相关; E% P7 l5 n. G2 \1 J
Negative linear correlation, 负线性相关% M) V1 d; q: D0 \
Negatively skewed, 负偏
# P! N' j; t" b6 W& \4 j6 P2 h2 [Newman-Keuls method, q检验
( w0 Y5 c4 i: B7 MNK method, q检验
$ a" l8 | o* N. BNo statistical significance, 无统计意义
0 s+ ]6 x$ R8 C9 l7 s7 X6 mNominal variable, 名义变量; {/ l/ D$ k8 o, R
Nonconstancy of variability, 变异的非定常性6 }/ r+ H/ t9 W# f% C+ l$ D
Nonlinear regression, 非线性相关+ }% ~3 k0 x6 s4 F2 [, D
Nonparametric statistics, 非参数统计
, v7 L/ ^. j* ^5 u' N: D) {: e9 HNonparametric test, 非参数检验6 l& d: i) P! Y; n/ o
Nonparametric tests, 非参数检验+ `! o4 g& m- L& i) j! r; n; o
Normal deviate, 正态离差, p* t7 Q5 s5 D5 M
Normal distribution, 正态分布7 `. m( J' _4 D# Y( n( ?" C, I3 i
Normal equation, 正规方程组& D. `6 G A \" x z
Normal ranges, 正常范围
- f& f' s7 C4 w0 p, S5 W8 UNormal value, 正常值. `, ]1 J% E- e, o+ _, j
Nuisance parameter, 多余参数/讨厌参数; P# j: a1 k0 v5 ]; x
Null hypothesis, 无效假设 ' V6 g$ k; q" t# @
Numerical variable, 数值变量
& v7 l% t* o, s: s# y1 R- R# ^Objective function, 目标函数
$ [, \" n- ]) b! b& k X2 s0 N, GObservation unit, 观察单位" |$ Y8 Q* q1 e4 M0 i
Observed value, 观察值
; s, F2 l' \% b* COne sided test, 单侧检验" y6 Y `: g5 W$ \
One-way analysis of variance, 单因素方差分析
* {" O1 r' N9 A6 [1 r4 hOneway ANOVA , 单因素方差分析+ x! t, Y0 C' T; g
Open sequential trial, 开放型序贯设计! t6 j3 W; l' [9 d: m
Optrim, 优切尾" L5 I7 F8 z: f- O! X! W- h8 |
Optrim efficiency, 优切尾效率
" y$ q J. Z6 nOrder statistics, 顺序统计量
+ d) ]- t7 f5 [& P2 I# nOrdered categories, 有序分类) L1 d1 Z" h5 f# j+ }+ \1 |" k# ?; a
Ordinal logistic regression , 序数逻辑斯蒂回归' v9 c( A8 B/ [: I1 G
Ordinal variable, 有序变量. t& B) R( Z3 \2 }. B7 d, Q
Orthogonal basis, 正交基8 b$ K3 x5 u0 ?! l3 s
Orthogonal design, 正交试验设计
s9 a1 ?' c0 L, j- L. S0 _ _5 fOrthogonality conditions, 正交条件$ D q( J+ f5 E- h% Q* ^
ORTHOPLAN, 正交设计 * g, h9 f" x/ d: L9 \+ b* a: p, Y7 k
Outlier cutoffs, 离群值截断点
& N9 b }) ]. T- r( Q7 Z$ F$ Z* QOutliers, 极端值9 Z" s8 j. V) n1 E+ o8 j2 s7 b- C7 @
OVERALS , 多组变量的非线性正规相关 ( a2 l# ~7 i/ [! i w/ m: H; I
Overshoot, 迭代过度
1 q9 {. r7 K- j/ o2 E/ S9 D' YPaired design, 配对设计
6 G& V# y0 Y* `8 @Paired sample, 配对样本
! }% |$ [7 ?) `0 E: V, JPairwise slopes, 成对斜率
9 r9 R: Z7 J2 [ [# hParabola, 抛物线
. F# i6 _% L+ DParallel tests, 平行试验
: a: Q: O5 H8 ]Parameter, 参数
9 m: Q4 c& X$ B) qParametric statistics, 参数统计
7 r# W$ w; k/ A9 L% O1 d3 R* KParametric test, 参数检验% \/ C5 h3 b' b% v1 D+ d
Partial correlation, 偏相关; |0 Z9 f7 H, m& C4 f$ \
Partial regression, 偏回归7 D" D* J6 }2 [0 k8 {
Partial sorting, 偏排序
) U9 p+ z% E2 x4 R5 m( APartials residuals, 偏残差
5 G2 m( C# `& o% gPattern, 模式
( r( r$ r/ C2 z3 D, rPearson curves, 皮尔逊曲线
# Y9 o( `- f5 g* o+ XPeeling, 退层7 I: Z/ d/ B+ r L. v: l, @
Percent bar graph, 百分条形图
/ ~) L. }7 z/ ^ l- E* mPercentage, 百分比; e1 P, s& `$ H+ h* G/ W
Percentile, 百分位数, u" s/ U7 e5 \. ~: n
Percentile curves, 百分位曲线9 o" n- M8 C. e5 p; y
Periodicity, 周期性1 ^ r. b4 g' H0 s- i) w/ Y
Permutation, 排列& c0 i/ V- p( O; s
P-estimator, P估计量6 Q% d( H4 m; n# @' g( \
Pie graph, 饼图
# G. e3 M8 J9 @) @Pitman estimator, 皮特曼估计量: {! q. P* f. V
Pivot, 枢轴量& r' h4 [. `- M0 Y# ?. J0 R
Planar, 平坦
4 e% g& J, f5 M4 k+ {Planar assumption, 平面的假设
& I4 X& W+ R$ Z) h& }PLANCARDS, 生成试验的计划卡 f2 @: G q, l1 a1 v
Point estimation, 点估计
+ g) S p) i* W3 f5 s" PPoisson distribution, 泊松分布* S: }# L+ [. @! r. B# Q( B
Polishing, 平滑. S) [/ n% i7 M b
Polled standard deviation, 合并标准差' n) e. l" a5 {& y7 [+ y6 u5 y
Polled variance, 合并方差* t0 z7 c$ d8 M% R
Polygon, 多边图8 T8 y' E0 p3 A3 L# A9 e; G, g
Polynomial, 多项式
$ D5 K' _1 g+ F& n# u8 OPolynomial curve, 多项式曲线
* Z$ c( g+ O# `# `4 iPopulation, 总体
4 p# a: A+ }$ n0 PPopulation attributable risk, 人群归因危险度
* D+ H" l7 v: R: }, ]Positive correlation, 正相关
! j. z# e' T5 mPositively skewed, 正偏
" [* w) h3 p9 Y, b) T1 _% `' y' ]6 RPosterior distribution, 后验分布
- o! D- z( y0 _& Y* A, k( P* lPower of a test, 检验效能& }' N( ?+ z+ K$ b+ P3 T
Precision, 精密度' i2 u7 D! ~/ ^
Predicted value, 预测值
# ^% O, M% L/ t- PPreliminary analysis, 预备性分析$ A4 S( V, R: r0 V- z- J, W
Principal component analysis, 主成分分析
/ z+ E9 ?1 R3 ~; G8 ^, tPrior distribution, 先验分布
2 p8 K% J8 A8 nPrior probability, 先验概率
% j( S! T, _' C `Probabilistic model, 概率模型+ w& k: s1 ?. r% h: S- Z& j
probability, 概率/ E7 j% z! s4 p/ k3 n; u
Probability density, 概率密度/ ?4 K8 `( ~, l% T: a
Product moment, 乘积矩/协方差' D9 C4 h/ Q; `& H. _
Profile trace, 截面迹图( E* y0 b* F1 m, W
Proportion, 比/构成比
' b& m m P7 X/ z+ \) f, rProportion allocation in stratified random sampling, 按比例分层随机抽样
( ^" h# u- @1 j" M' wProportionate, 成比例
, }- Z4 k3 L' k2 ?% X, ^' RProportionate sub-class numbers, 成比例次级组含量& d' i" D/ f# d2 z, t
Prospective study, 前瞻性调查
& z8 N, r: X5 R8 BProximities, 亲近性 i7 T5 N F7 l& S6 o; i- w
Pseudo F test, 近似F检验4 Y, L& A5 o! T M# n2 ^9 a6 g5 g+ m
Pseudo model, 近似模型+ C9 C) ^7 m+ [2 m% i. v+ X
Pseudosigma, 伪标准差* J* {' Q" e- t
Purposive sampling, 有目的抽样
* [4 T! U' M+ H' YQR decomposition, QR分解
4 x0 ?7 C) T7 s( Q3 RQuadratic approximation, 二次近似
" ^) B: D R% @8 f2 r; P0 iQualitative classification, 属性分类
- H, X0 A c. R+ ]# IQualitative method, 定性方法" y. w6 m3 \5 J' x J
Quantile-quantile plot, 分位数-分位数图/Q-Q图
; `% u0 @9 n. ]; IQuantitative analysis, 定量分析
3 \1 j# F& U; sQuartile, 四分位数
2 o. H# P- ?5 n- c7 F2 [Quick Cluster, 快速聚类
. z$ M+ O3 `) H. [( S% X# FRadix sort, 基数排序 e8 t0 O; \4 L
Random allocation, 随机化分组0 _4 v& \1 S7 J7 m0 F- o
Random blocks design, 随机区组设计! S3 }1 `+ T3 Y' _0 E8 s% a! z
Random event, 随机事件
: o2 M7 I( i# u# xRandomization, 随机化
4 ^& x, b# S& y) g+ Y4 K$ |8 I& h" zRange, 极差/全距$ u ]/ v/ B+ V2 J, C4 }! \
Rank correlation, 等级相关, U! j; ^ r4 U' m: f
Rank sum test, 秩和检验
9 C- _/ Y/ k3 L2 |) D) f8 WRank test, 秩检验/ u: A1 V. c# z1 y/ @4 V
Ranked data, 等级资料
* N* O0 h& {) t1 E- hRate, 比率
" F& t* V9 t1 X6 G! [Ratio, 比例
$ n5 O' m/ x/ b; Q' r: t5 Z, t8 ^Raw data, 原始资料
5 Q. W, I# V4 n. E, ERaw residual, 原始残差
9 @+ m# }- V' v1 J ^+ k8 J4 \Rayleigh's test, 雷氏检验
( W" s7 i6 h4 r2 r) Z; b2 DRayleigh's Z, 雷氏Z值
; i9 V3 p+ u( } U' B% |- d u- `% fReciprocal, 倒数
" @2 B: Q9 T: f- sReciprocal transformation, 倒数变换
4 U& B! `; K# {) XRecording, 记录
% L, o5 o0 _7 X2 wRedescending estimators, 回降估计量
0 L! K0 u: H0 y7 T8 |. N' ^Reducing dimensions, 降维
5 W; y& N1 s+ S) c4 ~2 b9 R4 g GRe-expression, 重新表达1 M- a8 ~5 g( ?' L/ H, A% @
Reference set, 标准组
! u5 E7 K$ C1 A' O0 BRegion of acceptance, 接受域) P2 F: f9 C. \
Regression coefficient, 回归系数% X6 j0 w) t9 M: n& V" x# S
Regression sum of square, 回归平方和
. b& B. y6 q2 @Rejection point, 拒绝点
4 }& O; l' \/ U# B* V: }) L0 jRelative dispersion, 相对离散度9 U" k d- ~, C, y
Relative number, 相对数
- @( ^& J& t7 S& S* N6 [Reliability, 可靠性/ H1 X s: ?3 O
Reparametrization, 重新设置参数: V0 `+ j2 N5 v( V7 }8 d9 B# y
Replication, 重复
0 F$ q1 ^4 |9 u. J+ R- ?Report Summaries, 报告摘要
]) f7 D4 i1 |1 ^* w! n- dResidual sum of square, 剩余平方和
+ a- i( {" r% C8 b7 N& F. IResistance, 耐抗性
3 x/ G( t+ O0 [/ kResistant line, 耐抗线
* r. s9 k2 d6 Y ]6 MResistant technique, 耐抗技术
; T6 E7 {; a3 v0 u G+ q' G3 oR-estimator of location, 位置R估计量
/ K( z$ q& c" p- ^4 M! O0 G. ^( jR-estimator of scale, 尺度R估计量& k/ `! M) j* U/ g2 L: Z* _
Retrospective study, 回顾性调查% m0 h3 z7 R3 r9 K3 ^
Ridge trace, 岭迹6 J" q. N1 r' r5 y& X% ^& y: i+ i
Ridit analysis, Ridit分析
+ V7 H8 J( t% c2 x: |+ D/ bRotation, 旋转. V+ b9 Y7 f! t
Rounding, 舍入8 s4 |3 X& s& U- @
Row, 行; @1 }" @$ A9 y7 ^$ _' }+ ?
Row effects, 行效应
4 M, r. [+ _" \1 G) r: ARow factor, 行因素4 _# z' q- \% d2 Y, h
RXC table, RXC表
2 X l f/ ?) V% I( T0 C& s& cSample, 样本
8 ?7 {' e. p( `" ~$ ?- RSample regression coefficient, 样本回归系数
% Y8 _$ v+ r+ l8 r# s/ c' M$ Z( ESample size, 样本量
* ]/ {5 ^% }/ X( ?Sample standard deviation, 样本标准差
5 k5 g9 o& [3 U* o% uSampling error, 抽样误差
) P4 L! k% O: p0 M( l2 F% o1 K+ TSAS(Statistical analysis system ), SAS统计软件包
, V+ o, W, Y# g0 c, l& BScale, 尺度/量表
, r) P7 z; L) AScatter diagram, 散点图
8 o; i9 N& W' Q/ e; L6 N$ QSchematic plot, 示意图/简图5 Y8 D! S( Y: `- t
Score test, 计分检验
0 C+ |& ]/ N% M; D4 \1 e1 U) a2 dScreening, 筛检
, Q( Q! E1 z: Y/ X9 `+ }: KSEASON, 季节分析
% J# F9 {2 y2 x$ XSecond derivative, 二阶导数
' t' k6 M6 B9 N0 FSecond principal component, 第二主成分& _& g( |( b* S3 R- Y
SEM (Structural equation modeling), 结构化方程模型
3 n# z5 L1 \0 iSemi-logarithmic graph, 半对数图: h, E# W( ]4 b
Semi-logarithmic paper, 半对数格纸% i1 U" Z4 a8 f/ B4 F
Sensitivity curve, 敏感度曲线
5 V$ R. l/ ]1 Q$ Z# sSequential analysis, 贯序分析
1 o% Z' Q/ _* USequential data set, 顺序数据集- n- \6 F1 N! Y. v3 V o6 f
Sequential design, 贯序设计4 }$ }# A6 ^3 y) b
Sequential method, 贯序法+ y, |0 ^% A& ?' A1 a# r
Sequential test, 贯序检验法8 w. P* ~1 _4 G- l
Serial tests, 系列试验6 W; j, B b, P* f4 @
Short-cut method, 简捷法
7 G& F. k) c/ [+ S7 l oSigmoid curve, S形曲线. K9 j) z L) h3 x& W9 c& c- D
Sign function, 正负号函数
% V/ q- s5 B, eSign test, 符号检验, n/ F% z+ j0 C! c
Signed rank, 符号秩/ ?7 _$ l+ X3 L) G. e' s6 Q9 q
Significance test, 显著性检验+ c% j3 z; {* \2 J! I
Significant figure, 有效数字
& [1 i9 q1 L$ ]9 ?- pSimple cluster sampling, 简单整群抽样6 J2 F2 B& ^4 |+ d( Q( O# M( v
Simple correlation, 简单相关6 K+ G! l1 v; j
Simple random sampling, 简单随机抽样
+ V! u% i. ]# w, k5 `4 w- |Simple regression, 简单回归$ G) I6 H! m6 X" @0 C h
simple table, 简单表5 }- e7 U6 I* E- Y8 w, o
Sine estimator, 正弦估计量# P$ J) t/ r V0 K
Single-valued estimate, 单值估计8 e0 J: p, @2 r' R3 O) q7 I9 j
Singular matrix, 奇异矩阵0 @; u+ R: v5 F5 v4 j! k0 y9 t
Skewed distribution, 偏斜分布- o+ `/ N+ _4 Y& G, x4 ?
Skewness, 偏度
! n- l! o8 G) v+ H- F1 eSlash distribution, 斜线分布
3 C& _/ S9 X! K* c0 RSlope, 斜率# X* n% t: r9 X2 l$ S
Smirnov test, 斯米尔诺夫检验& X# @1 q5 I: K# H. Y
Source of variation, 变异来源# n7 H; Z2 e$ I# a$ K
Spearman rank correlation, 斯皮尔曼等级相关. Y. Q! C Y) Y, A5 A
Specific factor, 特殊因子2 l+ q5 a6 }# ?4 v
Specific factor variance, 特殊因子方差/ k' {" F! `( B3 ]9 N
Spectra , 频谱
& k# A/ v# m' O6 Z, pSpherical distribution, 球型正态分布
4 Q% s2 }- {3 i7 mSpread, 展布
$ k7 O* X, |+ YSPSS(Statistical package for the social science), SPSS统计软件包
! Y) T& ~- J) N5 @Spurious correlation, 假性相关
1 I! J' d& \" OSquare root transformation, 平方根变换
! A1 }! l3 ~5 QStabilizing variance, 稳定方差; p& P/ ~# B: m! K. v
Standard deviation, 标准差, M- G* J Z% ~/ i+ R7 U! B. E
Standard error, 标准误
% u7 |3 @6 y. |4 _8 c* j% KStandard error of difference, 差别的标准误
* z8 W: D1 l0 [& C3 YStandard error of estimate, 标准估计误差
+ J# v5 G! E% [. e# B* u9 w- gStandard error of rate, 率的标准误& K( T6 N, K; p8 M% N
Standard normal distribution, 标准正态分布
7 a' V' f# F1 _- VStandardization, 标准化. \& f# R+ ]/ _8 L: a; X
Starting value, 起始值9 K+ A+ K. a, z7 ^) h
Statistic, 统计量' K$ U5 q6 @* S- T7 l; @& j) i: w
Statistical control, 统计控制
. m1 Q" u* v9 a4 J- w1 Y, b% eStatistical graph, 统计图# ^% `( e$ C2 Z
Statistical inference, 统计推断
. P3 c" V& ~) k, hStatistical table, 统计表
+ O3 ?6 X) j1 I S0 MSteepest descent, 最速下降法
: l# G$ k3 E( `# z. mStem and leaf display, 茎叶图# w* z) o9 T: \& P
Step factor, 步长因子
' p& s4 E8 ]; C5 uStepwise regression, 逐步回归8 t2 S# N# K6 r; s+ g
Storage, 存
+ J1 L/ Z! b. P* UStrata, 层（复数）
# V9 F9 T3 j1 K3 R+ fStratified sampling, 分层抽样
" V/ H; }; ^2 o, v4 K9 b1 F% _Stratified sampling, 分层抽样
3 M( B1 t7 ]) k+ g6 `Strength, 强度
, W* \# {' J, g9 U$ Z# A. V/ AStringency, 严密性2 G. c$ T1 ?% q' |$ S
Structural relationship, 结构关系8 f, ^8 T, U8 @+ e
Studentized residual, 学生化残差/t化残差+ E' E: G1 p# f$ q; ]7 t
Sub-class numbers, 次级组含量
# f0 d" T$ y; A# l& k7 H* M. YSubdividing, 分割
7 Q9 w6 h- o/ U6 x! U& JSufficient statistic, 充分统计量
) R8 o1 V6 f$ V2 ~; zSum of products, 积和
1 C8 c e9 V; @( C; H- ^& ]Sum of squares, 离差平方和
g( N$ u9 {4 B+ E. ]6 ASum of squares about regression, 回归平方和2 o6 v$ L! _; E
Sum of squares between groups, 组间平方和* Z, w9 }+ ~$ [0 n+ j r+ [
Sum of squares of partial regression, 偏回归平方和! Z1 m' E, u* _: c) I9 T( D
Sure event, 必然事件. e0 V s d* v6 S: S
Survey, 调查. _ l! ?+ \" z3 o; [% c
Survival, 生存分析
% T3 X' N* F$ p, t) C2 iSurvival rate, 生存率
$ |' S, J1 B. i! GSuspended root gram, 悬吊根图
2 J+ m- Y! ~$ r' W, oSymmetry, 对称9 i2 v/ Y6 M# k( C1 z
Systematic error, 系统误差
7 L! I! r! B0 CSystematic sampling, 系统抽样
( |4 [- b) d z+ {% C2 }Tags, 标签
4 U# M1 b$ s7 T7 l, b& T( ?Tail area, 尾部面积
4 V+ k) y1 h8 r8 A( D+ F* uTail length, 尾长" v' v: u8 j' I# T
Tail weight, 尾重3 _2 L/ t5 i8 S8 c
Tangent line, 切线* V E6 }5 h) t* s- F
Target distribution, 目标分布
* f9 C7 b1 X$ `( m, Q& i7 dTaylor series, 泰勒级数, z2 Y# T6 [2 k# [( j! Z
Tendency of dispersion, 离散趋势, J( K' M7 J& v3 s- ^3 H
Testing of hypotheses, 假设检验
: I: G( V% ~/ _/ Q. s9 J7 fTheoretical frequency, 理论频数
, @# P% e1 s7 \Time series, 时间序列, O# }( j# \- O* A4 K4 V/ \0 X
Tolerance interval, 容忍区间
2 r. F3 I9 ? Q% H* W- pTolerance lower limit, 容忍下限9 n3 b& K1 C) D( |
Tolerance upper limit, 容忍上限7 a4 d! o7 _% D* ^2 t* ~- w$ P
Torsion, 扰率# e) k( `" q& s0 N" s
Total sum of square, 总平方和% f4 U3 ]; K3 a% u R- {6 J
Total variation, 总变异
* t1 V. K0 o- Z7 j" WTransformation, 转换
# H& O! B% W7 a$ `4 wTreatment, 处理. m5 b: G: J* e5 A C
Trend, 趋势+ |0 f! T( _3 B% A6 F- [
Trend of percentage, 百分比趋势
* {: b, i, J6 [. s: |9 [Trial, 试验
) Y; M, W' _/ Y1 h; `' rTrial and error method, 试错法& T& X8 G y2 R R2 ?' }! O6 Z* F
Tuning constant, 细调常数
3 c S, @( ]4 iTwo sided test, 双向检验9 u' ~" I4 J' _" ]
Two-stage least squares, 二阶最小平方
7 B# m/ j3 e+ B- |) G1 \8 FTwo-stage sampling, 二阶段抽样
( c M5 p1 F% Q% RTwo-tailed test, 双侧检验
5 E! E' X: p0 c# ~. n( wTwo-way analysis of variance, 双因素方差分析" l8 \3 |" T! W( h4 e
Two-way table, 双向表3 a9 V5 i8 b# A& B: `
Type I error, 一类错误/α错误% `/ r* F0 S; c" c' w
Type II error, 二类错误/β错误0 {, ]8 l) [+ P& [, y4 P1 p6 P
UMVU, 方差一致最小无偏估计简称9 \+ K& |5 n8 @. U3 z$ n! k: m
Unbiased estimate, 无偏估计
/ c: S) s* o5 ~6 @. F! iUnconstrained nonlinear regression , 无约束非线性回归
# w5 d1 ?* y9 Q- j' \, A( XUnequal subclass number, 不等次级组含量$ K) M9 b$ @% B* T% u! U( k9 C9 ?9 W- [
Ungrouped data, 不分组资料, ?3 o' S) ^; g
Uniform coordinate, 均匀坐标
. Q9 u$ R$ _, i- Y/ o+ f. XUniform distribution, 均匀分布
" W/ @4 q' A/ Y, QUniformly minimum variance unbiased estimate, 方差一致最小无偏估计8 g7 ]) Y$ \; Z& w4 H( H
Unit, 单元
* X; [0 z& i5 R6 JUnordered categories, 无序分类0 C8 P V, U1 O! \. d
Upper limit, 上限! R# u8 X7 H6 v" }% a3 `
Upward rank, 升秩
! v! }7 F7 t: S' sVague concept, 模糊概念9 u; Q) G6 H3 W# `4 @1 ]
Validity, 有效性
" ~/ ~. O9 f# r1 z5 t6 Z2 GVARCOMP (Variance component estimation), 方差元素估计+ L$ s4 e1 R- `7 m
Variability, 变异性
' C9 B. O3 [1 k# YVariable, 变量
, p& O9 m! U( mVariance, 方差' B$ ?4 { _, n7 v9 _( A
Variation, 变异* K8 i8 ]+ \8 q
Varimax orthogonal rotation, 方差最大正交旋转
! W, `: A, K- B' h& _7 R( \Volume of distribution, 容积6 [5 Z3 N& s: l$ G$ _" J- m. h
W test, W检验
( E# }. R @# y" f; DWeibull distribution, 威布尔分布( X. s, P9 I( \# _
Weight, 权数
: ?" l! g- l) c/ ~* DWeighted Chi-square test, 加权卡方检验/Cochran检验+ M6 Q% R2 f+ f _
Weighted linear regression method, 加权直线回归, \: N- r" z6 U8 Y: {
Weighted mean, 加权平均数
8 a( M2 N4 _8 A6 A! WWeighted mean square, 加权平均方差
$ b6 O3 { E( t0 n# k% eWeighted sum of square, 加权平方和
9 w* V$ n3 J. I4 j! z' P( IWeighting coefficient, 权重系数% v- i+ G" `0 h& y$ D1 N' O# }, T
Weighting method, 加权法
* v8 i$ c6 X- _* o- X& c) }" R; K, rW-estimation, W估计量
* N7 K8 j7 t- g4 w( O- c8 EW-estimation of location, 位置W估计量/ V$ i1 b5 s) i, X) `# y+ _
Width, 宽度
6 k5 P. j1 U; F* C- r; k# I! H" HWilcoxon paired test, 威斯康星配对法/配对符号秩和检验5 J% e+ ]4 m: J
Wild point, 野点/狂点
6 Q% M4 d: t; b% WWild value, 野值/狂值: b! ^1 T O) V* {: ]% G' n
Winsorized mean, 缩尾均值8 R6 M3 k9 c" c& b; V) Q
Withdraw, 失访 0 C4 ?3 z9 }. B! J) t
Youden's index, 尤登指数
+ P( q& E2 J; W$ ?Z test, Z检验
* S' w$ x5 ]& A4 X' d4 y, GZero correlation, 零相关
1 x9 }+ V* H: N# zZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
